Differentiable activity analysis is a dataflow analysis which marks values in
a function as varied, useful, or active (both varied and useful).
Only active values need a derivative.
The invariant is that this analysis should be able to stay in sync with the list
of functions stored in SILModule's function list. If any functions are
added/deleted then analyses can get out of sync with the state of the underlying
SILModule.
Some notes:
1. This is currently disabled by default since there are a bunch of
violations of this in the compiler. I am in the process of fixing violations.
Some examples: the linker and global opt.
2. This is a no-op in non-assert builds.
3. The full verification will only happen when -sil-verify-all is enabled.
Otherwise, we only check that when we delete a function, we had state for the
function.
rdar://42301529
An interprocedural analysis pass that summarizes the dynamically
enforced formal accesses within a function. These summaries will be
used by a new AccessEnforcementOpts pass to locally fold access scopes
and remove dynamic checks based on whole module analysis.
This patch implements collection and dumping of statistics about SILModules, SILFunctions and memory consumption during the execution of SIL optimization pipelines.
The following statistics can be collected:
* For SILFunctions: the number of SIL basic blocks, the number of SIL instructions, the number of SIL instructions of a specific kind, duration of a pass
* For SILModules: the number of SIL basic blocks, the number of SIL instructions, the number of SIL instructions of a specific kind, the number of SILFunctions, the amount of memory used by the compiler, duration of a pass
By default, any collection of statistics is disabled to avoid affecting compile times.
One can enable the collection of statistics and dumping of these statistics for the whole SILModule and/or for SILFunctions.
To reduce the amount of produced data, one can set thresholds in such a way that changes in the statistics are only reported if the delta between the old and the new values are at least X%. The deltas are computed as using the following formula:
Delta = (NewValue - OldValue) / OldValue
Thresholds provide a simple way to perform a simple filtering of the collected statistics during the compilation. But if there is a need for a more complex analysis of collected data (e.g. aggregation by a pipeline stage or by the type of a transformation), it is often better to dump as much data as possible into a file using e.g. -sil-stats-dump-all -sil-stats-modules -sil-stats-functions and then e.g. use the helper scripts to store the collected data into a database and then perform complex queries on it. Many kinds of analysis can be then formulated pretty easily as SQL queries.
Record noescape closure scopes. This allows passes to process closures and their
parent scopes in a controlled order. AccessEnforcementSelection needs this
because it needs to process parent scopes before selecting enforcement within
noescape closures.
Eventually this could be used by the PassManager so that
AccessEnforcementSelection can go back to being a function transform.
Add an interprocedural SIL analysis pass that summarizes the accesses that
closures make on their @inout_aliasable captures. This will be used to
statically enforce exclusivity for calls to functions that take noescape
closures.
The analysis summarizes the accesses on each argument independently and
uses the BottomUpIPAnalysis utility class to iterate to a fixed point when
there are cycles in the call graph.
For now, the analysis is not stored-property-sensitive -- that will come in a
later commit.
It makes sense to turn the new epilogue retain/release matcher to an Analysis.
Its currently a data flow with an entry API point. This saves on compilation time,
even though it does not seem to be very expensive right now. But it is a iterative
data flow which could be expensive with large CFGs.
rdar://28178736
The analysis can tell all the callsites which calls a function in the module.
The analysis is computed and kept up-to-date lazily.
At the core of it, it keeps a list of functions that need to be recomputed for
the Caller/Callee relation to be precise and on every query, the analysis makes
sure to recompute them and clear the list before any query.
This is NFC right now. I am going to wire it up to function signature analysis
eventually.
a separate analysis pass.
This pass is run on every function and the optimized signature is return'ed through the
getArgDescList and getResultDescList.
Next step is to split to cloning and callsite rewriting into their own function passes.
rdar://24730896
"
analysis pass.
This pass is run on every function and the optimized signature is return'ed through the
getArgDescList and getResultDescList.
Next step is to split to cloning and callsite rewriting into their own function passes.
rdar://24730896
(Headers first)
It has been generally agreed that we need to do this reorg, and now
seems like the perfect time. Some major pass reorganization is in the
works.
This does not have to be the final word on the matter. The consensus
among those working on the code is that it's much better than what we
had and a better starting point for future bike shedding.
Note that the previous organization was designed to allow separate
analysis and optimization libraries. It turns out this is an
artificial distinction and not an important goal.
